The Internet is increasingly becoming a commercially driven environment with web sites of increasing complexity, both in breadth and depth. Information about the number and type of users who are accessing a given web site or page is important both to the individual users themselves, and to third parties for determining the viability of various web page designs and layouts, the computing power and bandwidth required to support the web site, etc. Such information is also useful for applications such as Internet-site catalogs.
Various techniques have been employed to determine who is using a particular Internet site or page. Many conventional systems, such as counters that are incremented whenever a particular web site or page is accessed, provide basic frequency of usage information. However, such systems fail to address a number of shortcomings. A first problem with conventional systems is that user information collected in the normal manner does not distinguish between one user accessing a given page many times or many users each accessing the same page once. A second problem is that conventional counting techniques provide no indication of how long users spend looking at a given page before leaving. Thus, techniques of the prior art provide only a limited amount of information with limited accuracy.
Additional information which is valuable, both to the web site operator and to Internet users, is the number and type (i.e. demographics) of users who have viewed or who are currently viewing a web site or page. A third problem with conventional techniques then arises since they do not provide an adequate mechanism for gathering and presenting this data to the users or third parties. In particular, while access counters can determine when a user accesses a given page, they provide no information about how long the user's attention is directed to the page or when the user “leaves” by accessing a different web page or site. Also, access counters do not collect information about the type of user, and therefore cannot report this information. Furthermore, due to proxy servers and other possible caching techniques, user accesses to web pages may be served locally without a user actually accessing the desired web site. Such hits will, thus, not be recorded by the web server.
Because of the limitations in the accuracy and scope of collected information, a fourth problem related to conventional information gathering techniques is that an Internet user cannot easily determine in real time what web sites and pages are popular with other users with similar backgrounds and interests. A fifth problem is that a user can not determine which other users are simultaneously viewing the same web page or site. A sixth problem is that, while a user may be able to view a directory or “map” indicating other web sites and/or pages which are linked or otherwise related to the one they are currently viewing, conventional systems do not permit the user to know how many users are currently at the neighboring pages, to filter the map to show sites with, e.g., a minimum number of active users, with users having particular characteristics, etc., or to determine which links are most popular with users having particular characteristics.
Moreover, while information about frequency of site or page visits is used to compile lists of popular sites, the catalogs are limited to grouping sites by content. A seventh problem, then, is that there is presently no mechanism to permit a user to determine “relevant” sites or pages according to the characteristics of the users of those sites or pages, as opposed to its contents.
An eighth problem with conventional applications is that they also do not permit a user to enter into a real-time chat with other users who are viewing the same page. While some real-time chat capabilities are present, they require the user IDs to be known in advance and are concerned only with whether a user is connected to the Internet, not what page or site they are presently accessing.
For example, the ICQ program, from ICQ, Inc., is an Internet chat program in which subscribing members are assigned a user ID. When a member logs onto the Internet, their ID is transmitted to the ICQ system. Individual users can compile “buddy lists” of other ICQ users and are informed when one of those IDs has logged on or off. However, this feature is limited only to IDs which are known in advance. ICQ users are also able to communicate with each other via, e.g., chat sessions. However, apart from lists of users in various “chat rooms”1, no information is provided about the activities of the users in general, only whether they are logged in to the Internet.
Another Internet application which purports to provide information about on-line users is the ALEXA application, available from ALEXA INTERNET. The Alexa service works in conjunction with a user's web browser and displays a separate window on the user's computer screen which contains information about the web site currently being viewed and suggests related sites. The Alexa system also tracks a user's usage patterns and uses this information to determine which sites will be of most interest to the individual user, as well as compiling statistical information about the number of Alexa users who have visited a particular web site. However, none of the aforementioned problems are adequately addressed by that system. While Alexa provides some information about web sites, the presented tracking information is merely another variant of the conventional “hit” counter. No information is presented about the numbers or types of other users who may be viewing the same web site or page at the same time, nor are mechanisms provided for one user to communicate with other users who are in the same location.
Thus, there are multiple problems and shortcomings in the prior art as noted above.